References
- Norwegian Oil and Gas industry, Environmental Work by
the Oil and Gas Industry- Facts and Development Trends,
Published by Norsk olje & gass, 2016.
- T. Austad, Water-based EOR in Carbonates and Sandstone: new
Chemical Understanding of the EOR-Potential Using “Smart
water”, in J. Sheng, Ed., Enhanced Oil Recovery Field Case
Studies; Gulf Professional Publishing, Houston, TX., 2013, pp.
301–335.
- S. Strand, E.J. Høgnesen, T. Austad, Wettability alteration of
carbonates - effects of potential determining ions (Ca2+ and
SO42–) and temperature, Colloids Surf., A, 275 (2006) 1–10.
- R.R. Nair, E. Protasova, S. Strand, T. Bilstad, Membrane
performance analysis for smart water production for enhanced
oil recovery in carbonate and sandstone reservoirs, Energy
Fuels, 32 (2018) 4988–4995.
- R. Nair, E. Protasova, S. Strand, T. Bilstad, Produced water
Treatment with Membranes for Enhanced Oil Recovery in
Carbonate and Sandstone Reservoirs, Proc. IOR 2017–19th
European Symposium on Improved Oil Recovery, Stavanger,
Norway, no. DOI:10.3997/2214–4609.201700296, April 24–27, 2017.
- J.P. Ray, R.F. Engelhardt, Produced Water-Technological/
Environmental Issues and Solutions, Published by Springer,
US, 1992.
- M. Reed, S. Johnsen, Produced Water-2-Environmental Issues
and Mitigation Technologies, Published by Springer, US, 1996.
- T. Puntervold, T. Austad, Injection of Seawater and Mixtures
with Produced Water into North Sea Chalk Formation:
Impact on Wettability, Scale Formation, and Rock Mechanics
Caused by Fluid-Rock Interaction, Presented at the SPE/EAGE Reservoir Characterization and Simulation Conference,
Abu Dhabi, SPE-111237-MS, 2007. Available at: https://doi.org/10.2118/111237-MS.
- O. Kedem, A. Katchalsky, Permeability of composite
membranes: Part 1. Electric current, volume flow and flow of
solutes through membranes, Trans. Faraday Soc., 59 (1963)
1918–1953.
- O. Kedem, A. Katchalsky, Thermodynamical analysis of the
permeability of biological membranes to non-electrolytes,
Biochim. Biophys. Acta, 27 (1958) 229–246.
- C.K. Diwara, S. Lo, M. Rumeau, M. Pontie. O. Sarr, A
phenomenological mass transfer approach in nanofiltration of
halide ions for a selective defluorination of brackish drinking
water, J. Membr. Sci., 219 (2003) 103–112.
- Z. Murthy, S. Gupta, Estimation of mass transfer coefficient
using a combined nonlinear membrane transport and film
theory model, Desalination, 109 (1997) 39–49.
- M. Dornier, M. Decloux, G. Trystram, A. Lebert, Dynamic
modeling of crossflow microfiltration using neural networks, J.
Membr. Sci., 98 (1995) 263–273.
- H. Al-Zoubi, N. Hilal, N. Darwish, A. Mohammad, Rejection
and modeling of sulphate and potassium salts by nanofiltration
membranes: neural network and Spiegler-Kedem model,
Desalination, 206 (2007) 42–60.
- W. Bowen, M. Jones, H. Yousef, Dynamic ultrafiltration of
proteins - a neural network approach, J. Membr. Sci., 146 (1998)
225–235.
- S. Bandini, J. Drei, D. Vezzani, The role of pH and concentration
on the ion rejection in polyamide nanofiltration membranes, J.
Membr. Sci., 264 (2005) 65–74.
- F. Donnan, Theory of membrane equilibria and membrane
potentials in the presence of non-dialysing electrolytes. A
contribution to physical.chemical physiology, J. Membr. Sci.,
100 (1995) 45–55.
- W.R. Bowen, A.W. Mohammad, N. Hilal, Characterisation of
nanofiltration membranes for predictive purposes – use of salts,
uncharged solutes, atomic force microscopy, J. Membr. Sci., 126
(1997) 91–105.
- J. Schaep, C. Vandecasteele, W. Mohammad, R. Bowen,
Modeling the retention of ionic components for different
nanofiltration membranes, Sep. Purif. Technol., 22–23 (2001)
169–179.
- K. Spiegler, O. Kedem, Thermodynamics of hyperfiltration
(reverse osmosis): criteria for efficient membranes, Desalination,
1 (1966) 311–326.
- S.-I. Nakao, S. Kimura, Models of membrane transport
phenomena and their applications for ultrafiltration data, J.
Chem. Eng. Japan, 15 (1982) 200–205.
- X. Wang, T. Tsuru, S.-i. Nakao, S. Kimura, The electrostatic and
steric-hindrance model for the transport of charged solutes
through nanofiltration membranes, J. Membr. Sci., 135 (1997)
19–32.
- X.-L. Wang, T. Tsuru, M. Togoh, S.-I. Nakao, S. Kimura, Evaluation
of pore structure and electrical properties of nanofiltration
membranes, J. Chem. Eng. Japan, 28 (1995) 186–192.
- R. Bowen, W. Mohammad, Diafiltration by nanofiltration:
prediction and optimization, AIChE J., 44 (1998) 1799–1812.
- W. Bowen, J.S. Welfoot, P. Williams, Linearized transport model
for nanofiltration: development and Assessment, AIChE J., 44
(2002) 760–773.
- M.H. Beale, M.T. Hagen, H. Demuth, Neural Networks
Toolbox (TM)– Users guide, The MathWorks, Inc.,
2018. Available at: https://usermanual.wiki/Document/Neural20Network20User20Guide.1353260851.pdf
- M. Cheryan, Ultrafiltration and Microfiltration Handbook, CRC
Press, USA, 1998.
- M. Manttari, A. Pihlajamaki, M. Nystrom, Effect of pH on
hydrophilicity and charge and their effect on the filtration
efficiency of NF membranes at different pH, J. Membr. Sci., 280
(2006) 311–320.
- B. Tansel, Significance of thermodynamic and physical
characteristics on permeation of ions during membrane
separation : hydrated radius, hydration free energy and viscous
effects, Sep. Purif. Technol., 86 (2012) 119–126.